Abstract
Stream Processing/Reasoning, an active research topic [5], has been picked up by different communities which developed a diversity of stream processors/reasoners. This however makes empirical evaluation and comparison of these engines a non-trivial task [4]. Different classes of those engines work on different formats of input data, use different languages to formulate queries, evaluate these queries using different semantics and produce different formats of output. To be able to compare such engines, a benchmarking framework that can cope with this wide diversity is needed.
This research has been supported by the Austrian Science Fund (FWF) projects P24090, P26471, and W1255-N23.
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Moßburger, A., Beck, H., Dao-Tran, M., Eiter, T. (2017). A Benchmarking Framework for Stream Processors. In: Ciancarini, P., et al. Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10180. Springer, Cham. https://doi.org/10.1007/978-3-319-58694-6_21
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DOI: https://doi.org/10.1007/978-3-319-58694-6_21
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